Multigraph bijections and matrices
Relabel a multigraph without losing parallel edges. Match vertices and edges, and express the same relabelling using matrices.
Concepts for §10.2
Before you begin
Rows, columns and entries
Fix a vertex order. Entry M[i,j] is in row i and column j. For a simple graph it records adjacency as 0 or 1; for a loop-free multigraph it can record the number of parallel edges. Matrix multiplication is explained in this lesson, not assumed as a prerequisite.
Adjacency
Two vertices are adjacent if an edge joins them directly. Being reachable by several edges is a different condition. For an undirected graph, reversing an edge’s endpoint names does not create a new edge.
Definitions and notation for this topic
Matrix of a finite relation
For on finite ordered sets, if and 0 otherwise. State the row order A and column order B.
An entry represents a particular ordered pair. A multigraph adjacency matrix may count parallel edges and therefore have entries greater than 1; that is a different convention.
Separate glossary example
For , , , the matrix is [[0,1],[1,0]].
Loops and parallel edges
A loop has the same endpoint twice. Parallel edges are distinct edges with the same endpoints. For an undirected multigraph, retain each edge’s identity and endpoint pair.
A simple undirected graph excludes both loops and parallel edges. The degree convention does not by itself specify how a matrix should record loops; state the matrix convention explicitly.
Separate glossary example
=AB and =AB are two edges, not one duplicated set entry. A loop =AA contributes two to .
Adjacency matrix
For a finite loop-free undirected multigraph with fixed vertex order, is the number of edges between vertices i and j. The diagonal is zero and M is symmetric.
For a simple graph entries are 0 or 1. A directed graph uses a row-to-column direction and need not give a symmetric matrix. Loop-diagonal conventions must be stated separately.
Separate glossary example
Two vertices (A,B) joined by two parallel edges have .
Matrix powers count walks
For the adjacency matrix of a finite simple graph, counts walks of length two from i to j, summed over possible intermediate vertices k.
These are walks, not necessarily paths: returning to a previous vertex is allowed. More generally counts length-r walks for nonnegative integer r; is the identity matrix.
Separate glossary example
In the path 1—2—3, from 1—2—3, and from 1—2—1.
Permutation matrix and relabelling
ᵀFor a vertex bijection f from G to H, put when and 0 otherwise, with rows in G order and columns in H order. For the same adjacency convention, ᵀ expresses preserved adjacency.
Pᵀ swaps P’s row and column indices. Right multiplication reorders columns and left multiplication by Pᵀ reorders rows. Reversing the convention for P changes the displayed identity; the matrix does not name an edge bijection.
Separate glossary example
If G order is (1,2,3), H order is (p,q,r), and ,,, then .
Worked example
Graph G has vertex order (A,B,C,D) and edges e1=AB, e2=AB, e3=BC, e4=CD, e5=DA. Graph H has vertex order (w,x,y,z) and edges h1=wz, h2=xy, h3=wy, h4=xz, h5=wy. Use , , , . Construct a compatible edge bijection and both adjacency matrices. Form P with rows in G order, columns in H order, and exactly when . Verify ᵀ.
Your task
G has vertex order (1,2,3) and edges , , , , . H has vertex order (p,q,r) and edges b1=pq, b2=pr, b3=qr, b4=pr, b5=pq. Take , , . Give an endpoint-preserving edge bijection. Construct , , and P using rows (1,2,3), columns (p,q,r), with iff . Verify ᵀ. How many edge bijections are compatible with this fixed f? Explain your count.
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Review your written reasoning
- I used each target vertex and each target edge exactly once.
- I preserved endpoints and the multiplicity of every vertex pair.
- I wrote the vertex order and counted parallel edges in adjacency entries.
- My orientation of P agrees with the matrix identity I checked.
- I justified four compatible edge bijections, without rejecting equivalent swaps of parallel edges.